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The metabolism of breast cancer metastasis to the lung: Key pathways and their implications in the metastatic microenvironment.

The metabolism of breast cancer metastasis to the lung: Key pathways and their implications in the metastatic microenvironment.
乳腺癌肺转移的代谢:关键途径及其在转移微环境中的影响。
批准号:
EP/Y029232/1
负责人:
Mariia Yuneva
金额:
$25.55万
依托单位:
依托单位国家:
英国
项目类别:
Fellowship
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

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中文摘要
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英文摘要
Metastasis is still responsible for the majority cancer-related deaths. Consequently, there is an urgent need to improve the treatment for the most aggressive cancer types, such as triple negative breast cancer. Metabolic adaptation is emerging as a hallmark to specifically target the metastatic process. According to our preliminary data, the metabolic features of breast cancer metastasis to the lungs include the upregulation of the methionine cycle, glutathione biosynthesis and a dependence on extracellular cystine. However, the interconnections between these pathways and the role they play in the lung colonisation process remain unclear. Also, the metabolic crosstalk between tumour cells and neighbouring cells in the lung microenvironment is poorly defined. Therefore, the first objective of this project is to explore the functional role of methionine and cysteine pathways in the breast metastatic cells and identify possible metabolic targets. Secondly, I aim to study the defined adaptations in the context of the lung microenvironment. To achieve that, I will use in vivo and ex vivo Myc-induced breast cancer mouse model. The metabolic vulnerabilities of the metastatic cells will be assessed using stable isotope-resolved metabolomics, genetic engineering tools and pharmacological interventions. Then, the metabolic interactions in the lung microenvironment will be defined using a unique approach that combines novel techniques such as mass spectrometry imaging, imaging mass cytometry, and single-cell RNA sequencing. Overall, the implications of this work will be the discovery of new metabolic mechanisms of metastasis that eventually contribute to the design of more efficient therapeutic approach for breast metastatic cancer.
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